October 7th, 2020

Accelerating AI Transformation in Healthcare

RSS icon RSS Category: Business, Community, H2O Driverless AI, Machine Learning

The healthcare industry is evolving rapidly with volumes of data and increasing challenges. Early adopters of AI and machine learning in the healthcare space have embraced new data-driven initiatives and are reaping the benefits not only in terms of patient care but also in their own operations.

Hospitals, physicians, and laboratories can now use patient data and medical records to continuously improve patient outcomes, deliver care without increasing costs, and streamline clinical workflows. By using H2O.ai, a GPU accelerated and open source leader in AI and automatic machine learning, healthcare companies are able to manage claims management, detect fraud, predict hospital-acquired infections, and, most importantly, save more lives.

Responding to COVID-19 with AI

With the global pandemic, healthcare professionals are facing multiple challenges in this fight against COVID-19 including a shortage of essential supplies, as well as staffing requirements per hospital as an example. 

AI models are important to glean insights from data, forecast patterns, and make critical decisions. It helps providers predict when, where, and how much they need to prepare for a sudden increase in demand. H2O.ai has co-innovated with leading healthcare organizations during the pandemic including hospital staff predictions, ICU transfer and triage, and population risk segmentation. Learn more here.

H2O.ai at HLTH with NVIDIA

To foster knowledge advancement in AI and healthcare, we are excited to announce that we will be joining NVIDIA at HLTH, a virtual conference organized by HLTH Foundation, from October 12-16. 

Learn more and register for the event here.

Read a blog by Renee Yao about the latest advancements from NVIDIA in the healthcare industry with AI.  

Leave a Reply

+
H2O LLM DataStudio Part II: Convert Documents to QA Pairs for fine tuning of LLMs

Convert unstructured datasets to Question-answer pairs required for LLM fine-tuning and other downstream tasks with

September 22, 2023 - by Genevieve Richards, Tarique Hussain and Shivam Bansal
+
Building a Fraud Detection Model with H2O AI Cloud

In a previous article[1], we discussed how machine learning could be harnessed to mitigate fraud.

July 28, 2023 - by Asghar Ghorbani
+
A Look at the UniformRobust Method for Histogram Type

Tree-based algorithms, especially Gradient Boosting Machines (GBM's), are one of the most popular algorithms used.

July 25, 2023 - by Hannah Tillman and Megan Kurka
+
H2O LLM EvalGPT: A Comprehensive Tool for Evaluating Large Language Models

In an era where Large Language Models (LLMs) are rapidly gaining traction for diverse applications,

July 19, 2023 - by Srinivas Neppalli, Abhay Singhal and Michal Malohlava
+
Testing Large Language Model (LLM) Vulnerabilities Using Adversarial Attacks

Adversarial analysis seeks to explain a machine learning model by understanding locally what changes need

July 19, 2023 - by Kim Montgomery, Pramit Choudhary and Michal Malohlava
+
Reducing False Positives in Financial Transactions with AutoML

In an increasingly digital world, combating financial fraud is a high-stakes game. However, the systems

July 14, 2023 - by Asghar Ghorbani

Ready to see the H2O.ai platform in action?

Make data and AI deliver meaningful and significant value to your organization with our state-of-the-art AI platform.